Object imaging is useful in a variety of applications. By way of example, biometric recognition systems image biometric objects for authenticating and/or verifying users of devices incorporating the recognition systems. Biometric imaging provides a reliable, non-intrusive way to verify individual identity for recognition purposes. Various types of sensors may be used for biometric imaging.
Fingerprints, like various other biometric characteristics, are based on distinctive personal characteristics and thus provide a reliable mechanism to recognize an individual. Thus, fingerprint sensors have many potential applications. For example, fingerprint sensors may be used to provide access control in stationary applications, such as security checkpoints. Fingerprint sensors may also be used to provide access control in mobile devices, such as cell phones, wearable smart devices (e.g., smart watches and activity trackers), tablet computers, personal data assistants (PDAs), navigation devices, and portable gaming devices. Accordingly, some applications, in particular applications related to mobile devices, may require recognition systems that are both small in size and highly reliable.
Most commercially available fingerprint sensors are based on optical or capacitive sensing technologies. Solutions using optical fingerprint sensors usually require an optical element to condition light before the light reaches the sensor elements. Unfortunately, it remains challenging to fit conventional optical elements into the limited height available in relatively small spaces, such as found in a display stack of an electronic device. Further, implementations with light conditioning structures at or above an active display matrix involve a trade-off between cover layer thickness, image blurring and image quality preventing practical product implementation.
As a result, fingerprint sensors in most mobile devices are capacitive sensors having a sensing array configured to sense ridge and valley features of a fingerprint. Typically, these fingerprint sensors either detect absolute capacitance (sometimes known as “self-capacitance”) or trans-capacitance (sometimes known as “mutual capacitance”). In either case, capacitance at each sensing element in the array varies depending on whether a ridge or valley is present, and these variations are electrically detected to form an image of the fingerprint.
While capacitive fingerprint sensors provide certain advantages, most commercially available capacitive fingerprint sensors have difficulty sensing fine ridge and valley features through large distances, requiring the fingerprint to contact a sensing surface that is close to the sensing array. It remains a significant challenge for a capacitive sensor to detect fingerprints through thick layers, such as the thick cover glass (sometimes referred to herein as a “cover lens”) that protects the display of many smart phones and other mobile devices. To address this issue, a cutout is often formed in the cover glass in an area beside the display, and a discrete capacitive fingerprint sensor (often integrated with a mechanical button) is placed in the cutout area so that it can detect fingerprints without having to sense through the cover glass. The need for a cutout makes it difficult to form a flush surface on the face of device, detracting from the user experience, and complicating the manufacture. The existence of mechanical buttons also takes up valuable device real estate.